标题: Emotional habitat: mapping the global geographic distribution of human emotion with physical environmental factors using a species distribution model

作者: Li, YZ (Li, Yizhuo); Fei, T (Fei, Teng); Huang, YJ (Huang, Yingjing); Li, J (Li, Jun); Li, X (Li, Xiang); Zhang, F (Zhang, Fan); Kang, YH (Kang, Yuhao); Wu, GF (Wu, Guofeng)

来源出版物: INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE DOI: 10.1080/13658816.2020.1755040提前访问日期: APR 2020

摘要: Human emotion is an intrinsic psychological state that is influenced by human thoughts and behaviours. Human emotion distribution has been regarded as an important part of emotional geography research. However, it is difficult to form a global scaled map reflecting human emotions at the same sampling density because various emotional sampling data are usually positive occurrences without absence data. In this study, a methodological framework for mapping the global geographic distribution of human emotion is proposed and applied, combining a species distribution model with physical environment factors. State-of-the-art affective computing technology is used to extract human emotions from facial expressions in Flickr photos. Various human emotions are considered as different species to form their 'habitats' and predict the suitability, termed as 'Emotional Habitat'. To our knowledge, this framework is the first method to predict emotional distribution from an ecological perspective. Different geographic distributions of seven dimensional emotions are explored and depicted, and emotional diversity and abnormality are detected at the global scale. These results confirm the effectiveness of our framework and offer new insights to understand the relationship between human emotions and the physical environment. Moreover, our method facilitates further rigorous exploration in emotional geography and enriches its content.

入藏号: WOS:000531934000001

语言: English

文献类型: Article; Early Access

作者关键词: Affective computing; emotional distribution; species distribution model; geosocial data; maximum entropy modelling

地址: [Li, Yizhuo; Fei, Teng; Huang, Yingjing; Li, Jun] Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Peoples R China.

[Li, Xiang] Informat Engn Univ, Inst Survey & Mapping, Zhengzhou, Peoples R China.

[Zhang, Fan] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan, Peoples R China.

[Wu, Guofeng] Shenzhen Univ, MNR Key Lab Geoenvironm Monitoring Great Bay Area, Shenzhen, Peoples R China.

[Wu, Guofeng] Shenzhen Univ, Shenzhen Key Lab Spatial Smart Sensing & Serv, Shenzhen, Peoples R China.

[Kang, Yuhao] Univ Wisconsin, Dept Geog, Geospatial Data Sci Lab, Madison, WI 53706 USA.

通讯作者地址: Fei, T (通讯作者)，Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Peoples R China.

电子邮件地址: feiteng@whu.edu.cn

影响因子：3.545